Risk Observability for
Artificial Intelligence

Real-time analytics platform, purpose-built for the three lines of defence to analyse, optimise & govern AI Risks in the regulated enterprise

Next-generation AI Risk monitoring integrated with multiple technology stacks


AI can & does go wrong

Any failure of AI-enabled automation in the regulated enterprise creates operational and compliance liability with novel, dynamic risks for both the data office and the three lines of defence. This necessitates AI risk monitoring at scale.

AI Controls Repository

Taxonomy of re-usable artefacts and internal controls libraries to ensure that your automated systems are within your risk appetite, while ensuring policy compliance.

AI Risk Observability

Single pane of glass for data scientists, operational risk and IT audit specialists to collaborate across the automation value chain, enabling risk transparency and visibility.

AI Outcomes Interpretability

Managed services to demonstrate, machine learning risk provenance for bespoke use-cases to executive stakeholders & regulators, fostering trust & accountability.

Are you AI ready?

Audit your readiness & discover newer, emerging risks
in your AI-enabled product or service.

Sign up for a free AI Risk check list!


    Turn AI Risk into Opportunity!

    Gain 360° visibility and transparency into all your AI Risks with a comprehensive pre-built taxonomy.

    Innovate with confidence & trust in your AI.

    AI Use-Cases
    Unique AI Risks


    See how it all comes together

    With Zupervise, you can now analyse risks across multiple layers of AI: models, training data, inputs & outputs.

    Step 1 - Analyse

    Identify your AI Risk universe

    Discover risks in your current business process design. Enable out of the box AI Risk Controls & manage a balance between AI risk appetite and automation experimentation.

    Step 2 - Optimise

    Unify AI Risk Data

    Foster a culture of AI Risk mitigation and make intelligent & informed risk decisions from a single shared system of record. Govern AI Risks originating from the quality of historical data and that of evaluation & benchmark data-sets.

    Step 3 - Govern

    Gain Visibility into AI Risk Trends

    Delineate accountability and make it easier to place trust in your AI investments with data-driven insights into emerging AI Risks. For each AI Risk, monitor multiple signals, including changes in attributes to be able to forecast a material effect on your risk appetite.


    Streamline AI Risk Transparency

    Identify AI Risks

    Build your own AI Risk and AI controls taxonomy, or re-use our artefacts, templates and libraries to develop forward-looking internal controls.

    Breakdown Governance Silos

    Single pane of glass dashboard that has source, risk and operational data integration capabilities to improve transparency in automation deployments & outcomes.

    Demonstrate Regulatory Compliance

    Articulate algorithmic risk provenance to executive stakeholders and regulators on-demand.


    we help
    you answer

    Discover diverse
    implications of
    AI Risks


    Will your AI comply
    with regulatory policy standards & legislation frameworks?


    Is your AI model secure from newer & as yet unknown attack vectors?


    Does your AI process personally identifiable data for automated

    Third Party

    Can you effectively vet your technology vendor's AI deployments?


    How is the AI decision outcome interpreted by humans
    in the loop?


    Is your AI ethical, responsible, accountable &


    Thought leadership,
    news & industry updates

    A collection of original content on AI Risk governance, curated news & research.

    Let’s do this

    Get started with

    Schedule a meeting with an AI Risk expert to see Zupervise in action

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